🚀 Holy 💩! Major Local AI Breakthrough! 🧠 744B-parameter GLM-5.2 (1.5 TB total) is now running on just ~25 GB RAM — no discrete GPU required! 👀 Wut!? Must test!! Italian engineer @JustVugg built Colibrì, a pure C inference engine (single ~2.4k line file, zero runtime deps) that: • 🛡️ Keeps the dense core (~10 GB at int4) resident in RAM • 📀 Streams 21,504+ MoE experts from fast NVMe on demand (only ~40B active per token) • ⚡ Supports native MTP speculative decoding + MLA attention Result: Frontier-class model on everyday consumer hardware! 📊 Current speeds: • 25 GB RAM setup → 0.05–0.1 tok/s (disk-bound) • Higher RAM + fast SSD → up to 1+ tok/s (warm) • It's a start... what could you do with a 5090? 💡 Big opportunity: Pair it with Phison aiDAPTIV+ AI SSDs to kill the I/O bottleneck 👉 smarter caching, prefetching & KV offload could make it dramatically faster! This is a huge step toward truly accessible local frontier AI. 🔗 GitHub: JustVugg/colibri

🚀 Local Inferencing Upgrade: AMD’s next high-end APU is in development Codenamed Medusa Halo (expected as Ryzen AI Max 500 series): • Zen 6 CPU cores • RDNA 5 graphics • LPDDR6 memory support Leaks suggest it could deliver ~80% higher memory bandwidth than the current Strix Halo (Ryzen AI MAX+ 395), thanks to faster LPDDR6. This should bring meaningful improvements in: 🎮 Gaming performance 🤖 Local AI inference 🖼️ Integrated graphics A smaller refresh (Gorgon Halo) is expected in late 2026, with full Medusa Halo likely arriving in 2027. #AMD# #APU# #RDNA5#

📰 A new coding Agent Index was just released by @ArtificialAnlys. This measures both the model and the harness. No open source harnesses included. OpenSource for Coding is now legit. 🔥 Claude Code+GLM-5.1 (53) > Claude Code+Sonnet 4.5 🔥 Claude Code+GLM-5.1 (53) > Gemini CLI+Gemini3.1 DeepSeek V4 Pro & Kimi K2.6 also hit 50

🚨 OMG! Qwen just released Qwen3.6-27B! This is an update to the King 👑 of Open Source Med Models! A 27B dense model that beats the much larger Qwen3.5-397B-A17B (~15x bigger) on coding benchmarks! 🤯 Watch out Opus 4.7 Key wins: • SWE-Bench Verified: 77.2 (vs 76.2) • SWE-Bench Pro: 53.5 (vs 50.9) • Terminal-Bench 2.0: 59.3 (vs 52.5) ✅ Strong multimodal reasoning ✅ Thinking + Non-thinking modes ✅ Apache 2.0 (fully open) Smaller model. Flagship performance. 🔥